import timeit
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn import datasets,linear_model
X,y = datasets.load_diabetes(return_X_y=True)
X
raw=X[:,None,2]
max_raw=max(raw)
min_raw=min(raw)
scaled=(2*raw - max_raw - min_raw)/(max_raw-min_raw)
fig, axs = plt.subplots(2,1,sharex= True)
axs[0].hist(raw)
axs[1].hist(scaled)
# Modelos para entrenamiento
def train_raw():
linear_model.Linear